---
library_name: mlx
license: mit
pipeline_tag: image-to-image
base_model: microsoft/Mage-Flow-Edit-Turbo
tags:
  - mlx
  - mlx-swift
  - image-editing
  - instruction-based-editing
  - diffusion
  - rectified-flow
  - mage-flow
---

# Mage-Flow-Edit-Turbo — MLX-Swift

An Apple-Silicon MLX-Swift port of
[microsoft/Mage-Flow-Edit-Turbo](https://huggingface.co/microsoft/Mage-Flow-Edit-Turbo):
native-resolution, 4-step instruction-based image editing.

> **Multi-component diffusion pipeline.** Per mlx-community conventions, a
> pipeline like this (NR-MMDiT + MageVAE + Qwen3-VL conditioner + scheduler) has
> no single-`model_type` slot, so it is published under this namespace rather
> than a re-hosted `mlx-community/*` repo. The large component weights come from
> the upstream `microsoft/Mage-Flow-Edit-Turbo` repo (MIT) and are **not**
> re-hosted here — only the port's genuine artifact is.

## What's in this repo

| file | what |
|---|---|
| `folded_adaln.safetensors` | The MageVAE adaLN constants baked at t=0 — the one weight the port adds (0.39 MB, replaces 37.7 M params of `t_embedder` + `adaLN_modulation`). |
| `*_config.json`, `model_index.json` | Component configs, for reference. |
| `sample_edit_512.png` | A validated edit ("make the background a snowy forest"). |

## Use

Code + gates: **[github.com/xocialize/mage-flow-swift](https://github.com/xocialize/mage-flow-swift)**.

```bash
# 1. download the upstream component weights
hf download microsoft/Mage-Flow-Edit-Turbo --local-dir Mage-Flow-Edit-Turbo
# 2. add this repo's baked artifact to the snapshot root
hf download xocialize/Mage-Flow-Edit-Turbo-mlx folded_adaln.safetensors \
  --local-dir Mage-Flow-Edit-Turbo
# 3. run
swift run -c release mage-flow-edit \
  --repo Mage-Flow-Edit-Turbo --ref dog.jpg \
  --prompt "make the background a snowy forest" --out edit.png
```

## Parity (vs the PyTorch oracle, CPU stream)

Every component is parity-locked; relative error, since this network's
activations reach ~1e5 and absolute tolerances mislead:

| component | worst rel error |
|---|---|
| MageFlow NR-MMDiT (12-block, 4.1B) | 6.8e-6 |
| MageVAE (encode + decode) | 1.08e-5 |
| Gaussian-Shading watermark | 0 (bit-exact) |
| FlowMatchEuler 4-step schedule | exact |
| end-to-end denoise (bf16 oracle vs fp32) | 2.8e-2 |
| full resolution range **512–2048** | 2048² @ 34.2 dB PSNR vs oracle |

## Notes

- **The DiT runs bf16** (upstream dtype). An earlier bf16 failure at ≥512² was
  root-caused to mlx-swift ≤0.31.6's JIT-miscompiled NAX split-K GEMM
  ([ml-explore/mlx#3797](https://github.com/ml-explore/mlx/issues/3797), fixed
  upstream by [#3810](https://github.com/ml-explore/mlx/pull/3810)); the port
  row-chunks the one affected GEMM (FFN `proj_out`) exactly, until an mlx-swift
  release ships the fix.
- **The Gaussian-Shading provenance watermark is reproduced bit-exactly** — the
  port does not strip Microsoft's watermark, so outputs remain detectable by the
  upstream detector.
- **The mandatory Responsible-AI content filter is wired in** (the upstream
  `CONTENT_FILTER_EDIT_SYSTEM` classifier, fail-closed) via the Qwen3-VL backbone.

Conditioning + filter run on
[qwen3vl-mlx-swift](https://github.com/xocialize/qwen3vl-mlx-swift).

## Pre-quantized DiT (no bf16 peak)

| file | recipe | gate |
|---|---|---|
| `transformer-int8.safetensors` | int8 g32 affine, attn+MLP Linears only | `int8 golden-deficit 1.296e-04 vs 2x baseline 1.982e-04 -> PASS` |
| `transformer-int4.safetensors` | int4 g64 affine, same scope | `int4 per-pass cosine 0.991115 (threshold 0.9900) -> PASS` |

Modulation/io/norm layers and the trailing block 11 stay bf16 (the final norm
amplifies last-block quant error ~1.6× into `proj_out`). Files are
self-describing (metadata carries bits / group size / kept blocks) and load
directly with **no bf16 peak** — int8 gate: golden-relative: deficit vs the fp32 oracle ≤ 2× the bf16 baseline's own deficit (bf16 itself is ~1e-4 from fp32 at this model's ~1.2e5 activation range); int4 gate: per-pass cosine ≥ 0.99 vs bf16 + e2e-validated render (43.9 dB int8 / valid int4 vs the bf16 render).
Quantization is weight-only: the mandatory content filter and the bit-exact
Gaussian-Shading watermark are unaffected. Measured t2i peak GPU @1024²:
bf16 19.6 → int8 17.2 → int4 16.1 GB.

```bash
# quant tier: skip the 7.7 GB bf16 transformer entirely
hf download microsoft/Mage-Flow-Edit-Turbo --include "text_encoder/*" --include "vae/*" --local-dir Mage-Flow-Edit-Turbo
hf download xocialize/Mage-Flow-Edit-Turbo-mlx folded_adaln.safetensors --local-dir Mage-Flow-Edit-Turbo
hf download xocialize/Mage-Flow-Edit-Turbo-mlx transformer-int4.safetensors --local-dir Mage-Flow-Edit-Turbo
swift run -c release mage-flow-edit --repo Mage-Flow-Edit-Turbo --dit-quant Mage-Flow-Edit-Turbo/transformer-int4.safetensors ...
```

MLXEngine: `MLXMageFlow` (same repo) wraps the family as `MageFlowT2IPackage`
/ `MageFlowEditPackage` — quant tiers auto-materialize these files via
`WeightSourcing`.

## Family

All six Mage-Flow checkpoints are supported by the same code:
[Mage-Flow](https://huggingface.co/xocialize/Mage-Flow-mlx) (t2i, RL) ·
[Mage-Flow-Base](https://huggingface.co/xocialize/Mage-Flow-Base-mlx) ·
[Mage-Flow-Turbo](https://huggingface.co/xocialize/Mage-Flow-Turbo-mlx) ·
[Mage-Flow-Edit](https://huggingface.co/xocialize/Mage-Flow-Edit-mlx) (edit, RL) ·
[Mage-Flow-Edit-Base](https://huggingface.co/xocialize/Mage-Flow-Edit-Base-mlx) ·
this repo (edit, Turbo). `text_encoder/` and `vae/` are byte-identical
family-wide; `folded_adaln.safetensors` is the same file in every repo.